audio = essentia.AudioFileInput(filename=input_file)
samples = audio()
frames = essentia.FrameGenerator(audio=samples,
frameSize=frame_size,
hopSize=hop_size)
window = essentia.Windowing(windowSize=frame_size,
zeroPadding=zero_padding,
type="hann")
fft = essentia.FFT()
cartesian2polar = essentia.Cartesian2Polar()
onsetdetectionHFC = essentia.OnsetDetection(method="hfc",
sampleRate=sample_rate)
onsetdetectionComplex = essentia.OnsetDetection(method="complex",
sampleRate=sample_rate)
onsets = essentia.Onsets(frameRate=frame_rate,
alpha=0.2,
delayCoef=6,
silenceTS=0.075)
total_frames = frames.num_frames()
n_frames = 0
hfc = []
complex = []
for frame in frames:
windowed_frame = window(frame)
complex_fft = fft(windowed_frame)
(spectrum, phase) = cartesian2polar(complex_fft)
hfc.append(onsetdetectionHFC(spectrum, phase))
complex.append(onsetdetectionComplex(spectrum, phase))
def compute(audio, pool, options):
sampleRate = options['sampleRate']
frameSize = options['frameSize']
hopSize = options['hopSize']
zeroPadding = options['zeroPadding']
windowType = options['windowType']
frameRate = float(sampleRate) / float(frameSize - hopSize)
INFO('Computing Onset Detection...')
frames = essentia.FrameGenerator(audio=audio,
frameSize=frameSize,
hopSize=hopSize)
window = essentia.Windowing(size=frameSize,
zeroPadding=zeroPadding,
type=windowType)
fft = essentia.FFT()
cartesian2polar = essentia.CartesianToPolar()
onsetdetectionHFC = essentia.OnsetDetection(method="hfc",
sampleRate=sampleRate)
onsetdetectionComplex = essentia.OnsetDetection(method="complex",
sampleRate=sampleRate)
onsets = essentia.Onsets(frameRate=frameRate)
total_frames = frames.num_frames()
n_frames = 0
start_of_frame = -frameSize * 0.5
hfc = []
complex = []
progress = Progress(total=total_frames)
for frame in frames:
if essentia.instantPower(frame) < 1.e-4:
total_frames -= 1
start_of_frame += hopSize
hfc.append(0.)
complex.append(0.)
continue
windowed_frame = window(frame)
complex_fft = fft(windowed_frame)
(spectrum, phase) = cartesian2polar(complex_fft)
hfc.append(onsetdetectionHFC(spectrum, phase))
complex.append(onsetdetectionComplex(spectrum, phase))
# display of progress report
progress.update(n_frames)
n_frames += 1
start_of_frame += hopSize
# The onset rate is defined as the number of onsets per seconds
detections = numpy.concatenate(
[essentia.array([hfc]),
essentia.array([complex])])
# prune all 'doubled' detections
time_onsets = list(onsets(detections, essentia.array([1, 1])))
t = 1
while t < len(time_onsets):
if time_onsets[t] - time_onsets[t - 1] < 0.080: time_onsets.pop(t)
else: t += 1
onsetrate = len(time_onsets) / (len(audio) / sampleRate)
pool.add(namespace + '.' + "onset_times",
essentia.array(time_onsets)) #, pool.GlobalScope)
pool.add(namespace + '.' + "onset_rate", onsetrate) #, pool.GlobalScope)
progress.finish()